Data Scientist

WFP celebrates and embraces diversity. It is committed to the principle of equal employment opportunity for all its employees and encourages qualified candidates to apply irrespective of race, colour, national origin, ethnic or social background, genetic information, gender, gender identity and/or expression, sexual orientation, religion or belief, HIV status or disability.

The World Food Programme is the world’s largest humanitarian organization saving lives in emergencies and using food assistance to build a pathway to peace, stability and prosperity, for people recovering from conflict, disasters and the impact of climate change. At WFP, people are at the heart of everything we do and the vision of the future WFP workforce is one of diverse, committed, skilled, and high performing teams, selected on merit, operating in a healthy and inclusive work environment, living WFP's values (Integrity, Collaboration, Commitment, Humanity, and Inclusion) and working with partners to save and change the lives of those WFP serves.

To learn more about WFP, visit our website: https://www.wfp.org and follow us on social media to keep up with our latest news: YouTube, LinkedIn, Instagram, Facebook, Twitter, TikTok.

WFP is a 2020 Nobel Peace Prize Laureate. WFP offers a highly inclusive, diverse, and multicultural working environment. WFP invests in the personal & professional development of its employees through a range of training, accreditation, coaching, mentorship, and other programs as well as through internal mobility opportunities. A career path in WFP provides an exciting opportunity to work across the various country, regional and global offices around the world, and with passionate colleagues who work tirelessly to ensure that effective humanitarian assistance reaches millions of people across the globe.

We offer
an attractive compensation package (please refer to the Terms and Conditions section of this vacancy announcement).

JOB TITLE: Data Scientist

TYPE OF CONTRACT: Regular Consultant (CST)

UNIT/DIVISION: Private Sector Partnerships (PSP), Individual Fundraising Team

DUTY STATION (City, Country): Remote (administrative DS is Rome, HQ)

DURATION: 11 months

SUPERVISOR: Head of Insights and Strategic Enablement

The United Nations World Food Programme (WFP) is the world's largest humanitarian organization fighting hunger worldwide. Private Sector Partnerships (PSP) is responsible for growing and nurturing engagement with individual supporters, corporate partners, foundations and philanthropists to mobilize resources for WFP's mission. As WFP continues to expand its individual fundraising (IF) programmes across WFP.org and ShareTheMeal, there is an increasing need to leverage advanced analytics, machine learning, artificial intelligence, and predictive modelling to optimize fundraising performance and long-term donor value. The Insights & Strategic Enablement function provides analytics, business intelligence, forecasting and strategic insight services to support evidence-based decision-making across PSP. The Data Scientist will play a critical role in transforming large and complex datasets into actionable insights, predictive models, and AI-driven solutions that improve fundraising effectiveness and supporter engagement. The role will work closely with fundraising, digital, technology, business intelligence, and data engineering teams within IF and more broadly PSP.

Reporting to the Head of Insights and Strategic Enablement, the data scientist will be responsible for providing data science, machine learning, and AI services in support of IF’s global data and analytics priorities, including deriving insights from large-scale datasets including transactional, web, app and experimentational. Collaborate with PSP stakeholders, data owners, product teams, and technical counterparts to translate business needs into analytical solutions, document methods and results, and support adoption of data-driven recommendations. Design, build, train, evaluate, and deploy machine learning and data science models that support segmentation, clustering, prediction, fundraising optimization and donor engagement. Apply the correct modeling technique; supervised or unsupervised to meet the differing business need. Apply advanced AI techniques, including natural language processing, large language models, retrieval-augmented generation, prompt engineering, and agentic workflows, where appropriate to automate analysis, improve decision support, and enhance knowledge discovery. Perform exploratory data analysis, feature engineering, model evaluation, hyperparameter tuning, and model optimization to ensure analytical outputs are accurate, explainab